{"id":"W4410220398","doi":"10.62951/repeater.v3i2.404","title":"Dinamika Sentimen Komunikasi Mahasiswa dan Dosen dengan Pemanfaatan Analisis Pesan Whatsapp Akademis Menggunakan Machine Learning","year":2025,"lang":"en","type":"article","venue":"Repeater","topic":"Educational Methods and Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001794874,0.0002033917,0.0002793081,0.0002130036,0.001021879,0.0003149153,0.000385368,0.0001519543,0.0004637957],"category_scores_gemma":[0.0007587606,0.0001842659,0.0001362356,0.0005811721,0.0001685364,0.0003806638,0.0001143042,0.0003732194,0.00003626284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002214233,"about_ca_system_score_gemma":0.0002231576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003382455,"about_ca_topic_score_gemma":0.0006601954,"domain_scores_codex":[0.9973151,0.0009823266,0.0003235125,0.0004161555,0.0004322329,0.000530686],"domain_scores_gemma":[0.9988276,0.0003265848,0.0001297156,0.0003512317,0.0001303082,0.0002345315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005973192,0.0002513939,0.8267917,0.0001041046,0.0003707234,0.00002763732,0.0429179,0.0000601424,0.004737423,0.02810175,0.005587993,0.09098952],"study_design_scores_gemma":[0.0006393989,0.00009349684,0.1975733,0.0002683295,0.0002029344,0.000006992648,0.03316969,0.0003135588,0.004645231,0.003835691,0.7585692,0.0006821959],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8712905,0.0006537813,0.0002039699,0.01113843,0.0005456504,0.0002960768,0.000008655005,0.0001668572,0.1156961],"genre_scores_gemma":[0.95568,0.0003693661,0.003455578,0.0005668222,0.0003298417,0.00002132795,0.00004503181,0.00002312492,0.03950894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7529812,"threshold_uncertainty_score":0.785957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02513185846518396,"score_gpt":0.3690973405691686,"score_spread":0.3439654821039846,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}